| # inference.py | |
| import joblib | |
| # Load your trained model | |
| model = joblib.load("house_price_predictor_model.joblib") | |
| def predict(data): | |
| # Assuming `data` is a list of features needed by your model | |
| prediction = model.predict([data]) | |
| return {'prediction': prediction.tolist()} | |